Regional Electric Bus Driving Plan Optimization Algorithm considering Charging Time Window

Abstract

Currently, although pure electric buses have the advantage of environmental-friendly, its endurance mileage is insufficient and the charging pile is still far away from the actual demand, resulting in a more complicated scheduling. Given this, we studied the driving plan of a pure electric bus, aiming to support the promotion and application of the electric bus. Considering service quality, we built a regional pure electric bus driving plan model and designed an optimal solution based on packing idea and genetic algorithm, aiming at minimizing fleet size, charging facility, and empty driving mileage. We took the electric bus routes operated in a region of Beijing as an empirical example. Compared with the results from the greedy algorithm, we found that the total cost of 544 bus trips with tasks was reduced by 19.6%. Although the average empty driving mileage increased by approximately 20%, the number of pure electric bus vehicles and the required amount of charging infrastructure decreased by 19.7% and 33.3%, respectively. The cost of increasing empty driving mileage was lower than that of the reducing number of buses and charging facilities, indicating that the above three variables reached a balance, and the optimization algorithm is proved to be significantly effective.